Characterization of Metastasis-Associated Cell Surface Glycoproteins in Prostate Cancer

Prostate cancer (PCa) is a major health problem in males in the United States. Its lethality is mostly attributed to the primary tumor metastasizing to distant sites that are highly resistant to conventional therapies. Serum Prostate Specific Antigen (PSA) is the only protein biomarker used in clinic for prediction of prostate cancer recurrence following local therapies. Nonetheless, PSA lacks the ability to predict the behavior of an individual tumor in an individual patient. Therefore, development of reliable biomarkers for detection of metastatic potential in primary tumors, as well as discovery of new therapeutic targets, is in a great need for improved disease survival and management. Tumor metastasis is a multistep process involving extravasation of a cancer cell subsequent invasion and expression at a site distal to the primary tumors. Cell surface glycoproteins play pivotal roles as recognition molecules in a range of cell communication and adhesion events. Aberrant cell surface glycosylation has been reported in various cancers including PCa, and strongly correlated with prognosis and metastasis. However, the staggering complexity of glycans renders their analysis extraordinarily difficult. This research project aims to develop a mass spectrometry-based glycoproteomic approach for the selective isolation and identification of cell surface glycoproteins from cellular samples, and apply this technology to the discovery of new glycoprotein biomarkers which are indicative of prostate cancer progression and metastasis. To this end, cell surface glycosylation patterns were characterized by lectin flow cytometry and lectin cytochemistry on a human syngeneic PCa cell metastatic model, PC3 and its two variants with different metastatic potentials. It was found that metastatic potentials of PC3 variants were inversely correlated with cell surface α2-6 sialic acid levels. Targeted to cell surface sialoglycoproteins, a new glycoproteomic approach was successfully developed, which combined selective metabolic labeling of cell surface sialyl glycans, chemically probing the labeled sugar with a biotin tag, affinity purification of sialylated proteins, SDS-PAGE separation, and subsequent LC-MS/MS for protein identification. Application of this methodology in our prostate cancer model system resulted in unique identification of a total of 80 putative cell surface sialoglycoproteins differentially expressed between PC3 variants. After prioritization of the candidate biomarkers, one cell-based prioritized biomarker CUB-domain-containing protein 1 (CDCP1) was verified in prostate cancer cell lines and clinical samples, including tissues and body fluids, by immunoassays. Results indicated that expression of CDCP1 protein is dysregulated in prostate cancer and it has potential utility as a therapeutic target and a diagnostic marker for PCa progression. Overall, the data from this research project provided the proof-of-principle evidence for our targeted glycoproteomic approach, which we believe will help expedite the discovery of new cancer biomarkers and therapeutic targets in diseases and delineation of signal transduction pathways on a global scale.